Abstract

In the northern Gulf of Mexico (GOM), numerous seafloor hydrocarbon seeps are well documented through seismic, seafloor, and chemical studies. In some areas, the seafloor seeps expend sufficient hydrocarbons to pass through the water column and present as sea-surface oil slicks, which with careful review and certain conditions can be identified on satellite images. Some areas with recurring potential sea-surface oil slicks as identified by oil-criteria screened satellite images are located above or near proven subsurface hydrocarbon-producing areas. However, other areas with established production have no sea-surface hydrocarbon slicks, and several areas with potential sea-surface slicks currently have no subsurface production. A publicly available data set of reservoir information for the northern GOM was correlated to a data set of sea-surface slick sites as identified on satellite data. Thirteen variables were selected from the database to evaluate depth relationships, fluid properties, and reservoir properties in relation to slick presence. Because initial multivariate analysis indicated the slick-to-reservoir-variables relationships were nonlinear, a random forest (RF) classification-tree analysis was performed to identify which variables are more important for slick development. The RF analysis used a collection of binary decision trees to determine the relative importance of the reservoir variables in identifying sea-surface slicks. The RF model was able to correctly classify or predict the presence of a slick and identified water depth, gas-oil ratio, and reservoir chronozone as the three most important variables when predicting the formation of a sea-surface slick.

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ISBN electronic:

9781560803119

Publication date:

January 01, 2013

With the increased resolution power of many geophysical methods, we are seeing direct evidence of seeps on a wide variety of data, including conventional seismic. New methods and technology have also evolved to better measure and detect seeps and their artifacts and reservoir charge and to map migration and remigration routes. In addition, detection of seepage is important for minimizing the risks associated with shallow gas drilling hazards, ensuring platform stability, and preventing well blow-outs.